{"ID":2860666,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.03903","arxiv_id":"2510.03903","title":"Zero-Shot Fine-Grained Image Classification Using Large Vision-Language Models","abstract":"Large Vision-Language Models (LVLMs) have demonstrated impressive performance on vision-language reasoning tasks. However, their potential for zero-shot fine-grained image classification, a challenging task requiring precise differentiation between visually similar categories, remains underexplored. We present a novel method that transforms zero-shot fine-grained image classification into a visual question-answering framework, leveraging LVLMs' comprehensive understanding capabilities rather than relying on direct class name generation. We enhance model performance through a novel attention intervention technique. We also address a key limitation in existing datasets by developing more comprehensive and precise class description benchmarks. We validate the effectiveness of our method through extensive experimentation across multiple fine-grained image classification benchmarks. Our proposed method consistently outperforms the current state-of-the-art (SOTA) approach, demonstrating both the effectiveness of our method and the broader potential of LVLMs for zero-shot fine-grained classification tasks. Code and Datasets: https://github.com/Atabuzzaman/Fine-grained-classification","short_abstract":"Large Vision-Language Models (LVLMs) have demonstrated impressive performance on vision-language reasoning tasks. However, their potential for zero-shot fine-grained image classification, a challenging task requiring precise differentiation between visually similar categories, remains underexplored. We present a novel...","url_abs":"https://arxiv.org/abs/2510.03903","url_pdf":"https://arxiv.org/pdf/2510.03903v1","authors":"[\"Md. Atabuzzaman\",\"Andrew Zhang\",\"Chris Thomas\"]","published":"2025-10-04T18:56:41Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[\"Language Model\"]","has_code":false,"code_links":[{"ID":608749,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2860666,"paper_url":"https://arxiv.org/abs/2510.03903","paper_title":"Zero-Shot Fine-Grained Image Classification Using Large Vision-Language Models","repo_url":"https://github.com/Atabuzzaman/Fine-grained-classification","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}